WINDOW FACTOR ANALYSIS:THEORETICAL DERIVATION AND APPLICATION TO FLOW INJECTION ANALYSIS DATA

Window factor analysis(WFA)is a self-modeling method for extracting the concentration profiles ofindividual components from evolutionary processes such as flow injection,chromatography,titrationsand reaction kinetics.The method takes advantage of the fact that each component lies in a specificregion along the evolutionary axis,called the‘window’.Theoretical equations are derived.The methodis used to extract the concentration profiles and spectra of seven bismuth species from data obtained byGemperline and Hamilton,who injected bismuth perchlorate into a flowing stream of hydrochloric acid.     

Migration and contamination of major and trace elements in groundwater of Madras city,India

Groundwater samples collected from both open and bore wells in an area of about 270 km² from Madras City, India, have been analyzed for major ions (HCO₃, Cl, Si, Na, Ca, and Mg) and trace elements (As, Se, B, V, Cr, Fe, Co, Pb, Cu, Zn, Cd, Mn, Ni, Mo, and Ba). The study reveals that the quality of potable water has deteriorated to a large extent. Seawater intrusion into the aquifer has been observed in nearly 50 percent of the study area. The toxic elements (As and Se) have already exceeded the maximum permissible limits of drinking water in almost the entire city. A positive correlation of As and Se with other toxic metals such as V, Cr, Fe, B, etc., indicates that all these elements are anthropogenic in origin. Applying multivariate analysis, the source for trace elements in groundwater has been grouped into two major factors: pollution and mobilization factors. The groundwater in the study area is largely contaminated by organic effluents and reflects the intensity of pollution caused by the overlying soil sediment and rapid infiltration of the pollutants.     

SVD迭代模型在夏季降水预测中的应用

文中设计了一种基于SVD迭代的短期气候预测模型,通过选择适当的影响因子,建立与预测对象之间的联系,从而实现对气象场序列的预测。分别对华北16个测站和长江中下游地区30个测站1991—2000年近10a夏季(6—8月)降水做预测试验,平均均方误差分别为0.352和0.312,平均符号相关系数分别为0.575和0.623。此研究表明,基于SVD迭代的气候预测模型是一种非常有效的短期气候预测途径,具有很强的应用价值。     

基于对应分析的训练样本的选择

本文提出一种基于对应分析的训练样本的选择方法。它从训练样本中自动地选择有代表性的典型训练样本,使得在自动分类中充分利用所采集的样本信息,以便得到满意的分类结果。通过实验与分析证明,该方法是可行的,它明显优于人工随机选择训练样本的方式。与基于Q型因子分析的训练样本选择方法相比,可以更快地得到较少的典型样本,满意的分类精度。     

Hydrochemical aspects of the negro river,patagonia, argentina

Water samples collected in the Negro River drainage basin (Patagonia, Argentina) during two different field trips—the first in May 1972 and the second in January 1973—were analysed for the major dissolved inorganic constituents. Q-mode factor analyses demonstrate that two factors account for over 98 per cent of the variance in both sample suites. They represent: a) the direct influence of solution of evaporites and associated carbonate rocks in an arid environment-type; b) the influence of the weathering products of metamorphic, igneous rocks, and varied non-calcareous sediments. R-mode factor analyses of the two sets of data suggest that although the main mechanisms controlling water chemistry were essentially the same, the principal sources of dissolved solids differed significantly in each separate occasion. Further, the major mechanisms controlling its water chemistry are within a wide spectrum of the so-called ‘rock dominance’.     

楚雄小水井—西西郎金矿带成矿空间

西西郎-小水井金矿带控矿因素为断裂和地层,岩浆期后热液、变质水及地下热卤水通过渗滤富集作用形成的微粒浸染型金矿床。该区是有理想的成矿空间。     

一种基于最佳指数模型的 TM 遥感影像最佳波段组合计算方法

如何通过定量计算选择最佳波段组合一直是TM等多波段遥感影像信息提取的研究热点。本文综合利用Erdas提供的可视化空间建模工具（ Spatial Modeler ）和面向对象的编程技术,提出了一种基于最佳指数（ Opti-mum Index Factor ,OIF）的定量计算与定性分析相结合的TM遥感影像最佳波段组合方法。实验证明,该方法快速有效,极大提升了TM等多波段遥感影像最佳波段组合的计算过程。     

Using simulated data to investigate the spatial patterns of obesity prevalence at the census tract level in metropolitan Detroit

Obesity is a serious public health problem in the United States. It is important to estimate obesity prevalence at the local level to target programmatic and policy interventions. It is challenging, however, to obtain local estimates of obesity prevalence because national health surveys such as the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System (BRFSS) are not designed to produce direct estimates at the local levels (e.g. census tracts) due to small population samples and the need to preserve individual confidentiality. In this study we address the problem of estimating local obesity prevalence rates by implementing a spatial microsimulation modeling technique to proportionally replicate the demographic characteristics of BRFSS respondents to census tract populations in metropolitan Detroit. Obesity prevalence rates are examined for high and low spatial clusters and studied in relation to the U.S. Department of Agriculture's (USDA) measures of low-income neighborhoods and local food deserts and CDC's measure of healthy and less healthy food environments currently used to target obesity reduction initiatives. This study found that obesity prevalence was largely clustered in the City of Detroit extending north into contiguous suburbs. The spatial patterns of highest obesity prevalence tracts were most similarly aligned with USDA-defined low-income tracts and CDC's less healthy food tracts. The locations of USDA's food desert tracts rarely overlapped with the highest obesity prevalence tracts. This study demonstrated a new methodology by which to assess local areas in need of future obesity interventions.     

大孔径闪烁仪观测中的相似理论适用性分析

利用2009年馆陶站(1-12月)和阿柔站(1-6月和10-11月)的大孔径闪烁仪LAS相关数据,分析了LAS观测中莫宁—奥布霍夫相似理论MOST理论的适用性,并探讨了MOST理论适用性的定量判断方法.结果表明:(1)在不稳定条件下,大尺度涡旋运动、大气湍流发展状况和温度尺度都能对MOST理论适用性产生显著影响;(2)确立了两种新的MOST理论适用性判断方法,即因子分析法和温度结构参数法,并验证了这两种判断方法是合理、可靠的.     

MIXTURE ANGLYSIS USING FACTOR ANGLYSIS I: CALIBRATION AND QUANTITATION

One of the major application areas of factor analysis, multivariate calibration and quantitation, is coveredin this review. The algorithms, methodologies and applications covered include principal componentregression, target transformation factor analysis, singular value decomposition and rank annihilationfactor analysis. Many important areas of research having relevance to multivariate calibration andquantitation problems are also covered in this review, including background correction, measurementerror, rank determination, cross-validation, figures of merit, detection of invalid samples, experimentaldesign, sample selection, statistical inference and wavelength selection.